The Oldconcept module takes a word that has been recognized as
a known concept and creates a new, up-to-date associative node
that preserves the instantaneous relationship of each concept to
nearby concepts caught up in the momentary syntactic assertion.

Typically a verb mediates the relationship from one concept to
another in the knowledge base (KB) that builds up over time as
the accumulation of all known facts and ideas about a concept.
Likewise the concept of any given verb is also mediated by its
associative relationships within myriad syntactic assertions.

In our Open Source AI epistemology, machine learning is the
gradual build-up of an ontology of intricately related facts.

We claim that the AI Mind is theoretically an improvement upon
the vaunted Cyc (R) ontology because we conceptualize concepts
in accordance with the SourceForge/ Mind/ Docs/ Theory of Mind
based on sound neuroscience and the linguistics of Noam Chomsky.

Our AI algorithm includes not only machine learning but also
forgetting -- as the consignment to oblivion of memories that
fail to be brought forward in the stream of consciousness for
lack of associative renewal on the basis of frequency of use.

2. Nil Novi Sub Sole

There is "nothing new under the sun" when we generate a sentence,
because the Chomskyan syntax of thought may only manipulate old
concepts already known to the mind but not new concepts until the
newConcept module converts them -- immediately -- to old concepts.

Then the oldConcept module processes the reentry of the output of
the mind back into the mind, reactivating each recognized concept
in chains of association so that spreading activation constitutes
a chain of thinking or meditating or mulling about old knowledge.
If the mind goes down a road less traveled in the conceptual wood
so as to think up an entirely original idea (E = mc^2, anybody?),
then perhaps that original idea has made all the difference.

For a known and recognized word in the input stream, the
Oldconcept module creates a new associative node for a
concept in the mindcore array Psi and also in the En
English lexical array that manipulates English words stored
in the Aud array of the auditory memory channel.

Each run of the AI Mind software starts out with a group
of old concepts already available in the semantic memory.
Although in the long run a major goal of AI might be to
have the AI Mind learn all its concepts and all its words
of natural language from scratch like a human baby filling
in a tabula rasa mind with the acquisition of language,
the goal of this particular open-source AI Mind project was
always to achieve and demonstrate the simplest possible level
of thinking based on the principle of
spreading activation.
That goal was achieved with an
AI breakthrough on 7 June 2006.

Not all of the above concepts are included in each AI Mind.
The English bootstrap sequence may contain some of the above
concepts, and also some extra concepts that were necessary
to construct sentences containing some of the above concepts.
When extra concepts need to be included in the bootstrap
sequence, the area for 64 reserved concepts is simply
enlarged to, say, 71 concepts. Above that number of
potentially reserved concepts, the AI automatically starts
assigning concept numbers for new concepts learned by the AI.

The
AI Debugger program may shed some light in general on how to debug
and troubleshoot programs in artificial intelligence.

If you try to teach the AI a new concept and it fails to
learn it, check to see if you have introduced only one new
concept at a time, as may be suggested in the user manual.

If the AI has already learned a concept but is failing to
recognize the word in the input stream, you may go into
Troubleshoot mode with the JavaScript Mind.html to see
what concept-number is being assigned to the concept.
With Mind.Forth, you may press Escape to halt the AI and
then enter .psi or .en or .aud to inspect the concepts.
In either case, it may be that the audRecog module is
mistakenly declaring the wrong concept-number because
of similarity in the word with some other known word.
If so, it may be necessary to debug the audRecog module
or to choose other words that will not confuse audRecog.